Lidar site model to aid counter drone system

ABSTRACT

A system for creating a three dimensional model of an environment includes a LIDAR scanning system to scan an environment to provide an image of a scene of the scanned environment, a geo-locator to tag a plurality of points within the image with geo-reference points and a labeler to label features of interest within the image of the scene and to identify possible access paths within the three dimensional model of the environment from the features of interest potentially providing an access path for a target drone.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority from U.S. Provisional PatentApplication Ser. No. 62/364,368, filed on Jul. 20, 2016, and U.S.Provisional Patent Application Ser. No. 62/306,841, filed on Mar. 11,2016, both of which are incorporated herein by reference in theirentirety.

FIELD OF THE INVENTION

This disclosure relates generally to drones and more particularly to atechnique to detect and track drones.

BACKGROUND

In recent years, the advancement of unmanned aerial vehicles or droneshas matured where drones are readily available at nominal costs to bepurchased by private individuals. The readily availability of drones tobe used by private individuals bring on additional concerns for lawenforcement and security personnel where drones can be used for unwantedor illegal activity. For example, a drone carrying contraband can beused by an individual to fly over a prison and deliver the contrabandwithin the prison walls. Drones can be flown into private areas, carryexplosives, or deliver contraband to personnel located in the privateareas. Furthermore, drones can be flown into air space that thenprevents manned airplanes from flying a desired course. Otherpossibilities of the use of drones are only left to the imagination ofunlawful actors and hence it is desirable for a system to locate a droneand render it useless when the drone is identified as a nuisance ordanger.

SUMMARY

In accordance with the present disclosure, a system for creating a threedimensional model of an environment includes a LIDAR scanning system toscan an environment to provide an image of a scene of the scannedenvironment, a geo-locator to tag a plurality of points within the imagewith geo-reference points and a labeler to label features of interestwithin the image of the scene and to identify possible access pathswithin the three dimensional model of the environment from the featuresof interest potentially providing an access path for a target drone.With such an arrangement, a three dimensional model of an environmentcan be provided to aid in preventive planning for countering undesireddrones.

The system may include one or more of the following featuresindependently or in combination with another feature to include: whereinthe LIDAR scanning system comprises a tracking system to track objectsin the scanned environment and the tracking system determines if a newtrack is a false track by looking where the track originated; whereinthe tracking system generates an intercept track for an intercept dronefrom the possible access paths determined from the labeler and theenvironmental model; a response planner to plan safe paths through theenvironment for an intercept drone; wherein the response plannerincludes identifying false positives; a response planner to plan theplacement of sensors within the environment to reduce blind spots in theenvironmental model; a response planner to plan interceptions thatminimize collateral damage; a response planner to select an appropriatecountermeasure including deploying a second drone to intercept thetarget drone; or a response planner to pilot an intercept drone aroundobstacles that have been mapped in the scene apriori.

In accordance with the disclosure, a method of providing a threedimension model of an environment includes: scanning an environment toprovide an image of the scanned environment; tagging a plurality ofpoints within the image with geo-reference points to identify thelocation of a plurality of points; labeling features of interest withinthe image and identifying possible access paths within the threedimensional model of the environment from the features of interestpotentially providing an access path for a target drone.

The method may include one or more of the following featuresindependently or in combination with another feature to include:tracking objects in the scanned environment and determining if a newtrack is a false track by looking where the track originated; generatingan intercept track for an intercept drone from the possible access pathsdetermined from features of interest within the image; planning safepaths through the environment for an intercept drone from the featuresof interest within the image; identifying false positives; planning theplacement of sensors within the environment to reduce blind spots in theenvironmental model; planning interceptions that minimize collateraldamage; selecting an appropriate countermeasure including deploying asecond drone to intercept the target drone; or piloting an interceptdrone around obstacles that have been mapped in the scene apriori.

In accordance with the present disclosure, a drone detection systemincludes: a LIDAR scanning system to scan an environment to provide animage of a scene of the scanned environment and to detect a target droneentering the scanned environment; a geo-locator to tag a plurality ofpoints within the image with geo-reference points; a labeler to labelfeatures of interest within the image of the scene and to identifypossible access paths within the three dimensional model of theenvironment from the features of interest potentially providing anaccess path for the target drone; and a response planner to select anappropriate countermeasure including deploying a second drone tointercept the target drone.

The drone detection system may additionally include the feature of atracking system to track objects in the scanned environment and whereinthe tracking system generates an intercept track for an intercept dronefrom the possible access paths determined from the scanned environment.

The details of one or more embodiments of the disclosure are set forthin the accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram of a drone detection system;

FIG. 2 is a diagram of using a LIDAR element to provide an electronicfence to protect an area of concern;

FIG. 3 is a sketch of a tracking LIDAR with a field of view of a camerapicture of a target and the corresponding LIDAR image taken from a LIDARscanner;

FIG. 3A is a diagram of a planned intercept course;

FIG. 4 is a diagram of an early detections system with a tracking LIDARto track a target;

FIG. 5 is a diagram of a plurality LIDAR elements disposed to provide anelectronic fence with a long range tracking LIDAR;

FIG. 6 is a diagram of a drone detections system with a threedimensional scene model for analyzing an environment;

FIG. 6A is a diagram of a geo-locator and labeler included within thedrone detection system of FIG. 6;

FIG. 6B is a diagram of an object avoidance path;

FIG. 6C is an example of a three dimensional scene;

FIG. 6D is another example of a three dimensional scene;

FIG. 7 is a screen shot of a computer screen with an example of a threedimensional scene;

FIG. 8 is a diagram of a drone viewing a target drone;

FIG. 9 is a block diagram of a system to implement a drone detectionsystem;

FIG. 10 is a diagram where a user designates a target drone using apointing device; and

FIG. 11 is a block diagram of a computer that can be used to implementcertain features of the system.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

The present disclosure describes techniques to use LIDAR as a sensor totrack drones. Light detection and ranging (LIDAR) can be used to createthree-dimensional (3D) imagery of a field of view. A LIDAR systemincludes a light source, such as a laser, that generates and directspulses of light. The light pulses are reflected by the surface ofvarious objects, such as the ground, a tree, or a building or an objectin the air such as a drone. A sensor in the LIDAR system detects thereflections. The relative location of the reflecting surface can bedetermined by the lidar from the elapsed time from when the light pulseis generated and when it is detected. This cycle of pulse and detectionmay be repeated thousands of times per second. The coordinate frame ofdetection can be translated into another coordinate frame for displayusing common methods. The reflected light pulses are used to create a 3Dimage of the scanned area or field of view. An operator may then use panand zoom commands to change the camera or sensor orientation and seedifferent portions of the scanned area or field of view.

A LIDAR has advantages over other sensors for tracking drones. Shortrange LIDARs (˜100 m) can interrogate all of their airspace and detect adrone, however the range of 100 meters has limited value. If we use along range LIDAR (1000 m) however because of the narrow field of view,it is not practical for the long range LIDAR to do detection. Ourdisclosure uses a two-tiered approach of using an alerting system to cuethe long range LIDAR so we may take advantage of the long range LIDAR.To make a long range LIDAR feasible we use a second sensor to alert(cue) that there is a drone present to track. The second sensor does notneed to do a good job of long range tracking, it only needs to provide asmall area to search with the long range LIDAR to find the drone. LIDARalso provides very precise three dimensional (3D) location informationand is capable of detecting the physical presence of an object in mostall lighting conditions. It doesn't require the drone to emit RF and itworks if the drone is stationary or slow or fast or regardless of beingclose to the ground or high in the air.

LIDAR has advantages over radar in that LIDAR allows for more accuratelocation and has a smaller spot size allowing for a more accurate imageof a target to be formed.

Referring now to FIG. 1, a drone detection system 100 (sometimesreferred to as a counter drone system) is shown to include a pluralityof detection sensors 110 arranged to detect an object, more specificallya drone 130. A detection processor 112 captures the existence of anobject and cues the presence of a drone 130 to a tracking sensor 114which acquires and tracks at long range the drone 130 using targettracker 116. An image of a target drone once cued can be fed to a targetidentifier 118 for target recognition and the image 120 of the cuedtarget can be displayed to an operator 122 on display 124 so theoperator 122 can verify and analyze the cued target. The target tracker116 also feeds the target tracks to a semi-autonomous response plannersystem 126 with inputs also from the operator 122 can determinecountermeasures 128 appropriate for the cued target. For example, ainterceptor drone 132 can be deployed.

From the latter, it can be seen, a counter drone system is providedwherein a cueing sensor provided by the detections sensors 110 is ableto detect the presence of an object wherein the cueing sensor cues thepresence of a target drone. A long range LIDAR system provided by thetracking sensor 114 and the target tracker 116 with a sensor pointed ina direction of the target drone to acquire and track at long range thetarget drone can provide an accurate location of the target dronewherein once a track is acquired, the motion of the target drone alongwith a Kalman Filter is used to maintain the track of the target drone.A threat detector provided by the target identifier 118 uses LIDAR datawhich is provided to the threat detector to determine if the targetdrone is a threat. Furthermore, countermeasures 128, in response to theoperator 122 or the semi-autonomous response planner 126, can then beimplemented to render useless the target drone when the target drone isidentified as a nuisance or danger. Optionally cameras can be aimed atthe track as well. LIDAR (and optional camera) data is given to humanoperator 122 to determine threat vs. non-threat or automated techniquescan be used as well. Sensor fusion techniques can also be used tocombine the camera and lidar data to assist in threat determination.

A camera can be aimed toward the target to get further information aboutthe target. Where to aim the camera can based on the target tracker andknowledge about the camera coordinate frame and the tracker sensorcoordinate frame as to be discussed further herein below.

It should be appreciated drone detection and tracking is accomplishedwherein one sensor 110 being a LIDAR or (alternatively, acoustics,infrared, etc) cues the presence but not high resolution location of adrone, and a LIDAR tracking sensor 114 (flash, Geiger mode, linescanning) is aimed to acquire and track at long range the target toprovide an accurate location. Once the track is acquired, the sensing ofthe target, and the prediction of the motion of the target usingstandard means (such as a Kalman Filter) is used to maintain the trackof the target.

It should be understood any Line scanning LIDAR is a suitable cuingsensor. Examples include a Quanergy M8, or a Velodyne VLP16. This isconfigured as a light fence facing upward and is described in FIG. 2.

A line scanning Lidar such as a Velodyne VLP-16 or similar can beconfigured as an upwards facing light fence. An object that breaks thelight fence will be registered by the LIDAR and it's location can betranslated into a coordinate, and in the case of a multibeam LIDAR, avector. This defines a search space for the long range LIDAR to hunt forthe object that has broken the light fence. Several such lidarsconfigured as a light fence may be networked together to form aparimeter around a location to protect the location such as the WhiteHouse, an airport, or a prison. Acoustic sensor systems could also beused to cue the sensor. In this case the audible signature of the droneis detected by a microphone array and translated into an approximatelocation. Similarly a radar could be used to cue the sensor.

Once cued, the long range LIDAR will “hunt” for a flying object that isdefined as an object that is off the ground, and in open space that ispreviously known to have been empty space. If the object is moving it istracked. If the object is stationary it is observed stationary.

It should be understood the response planner 126 will do the followingtasks when an object is observed:

-   -   Display the raw lidar data 24 (FIG. 3) to a human operator.    -   Aim a camera at the location of the target and present the        operator with the camera view 22 (FIG. 3).    -   Plan an intercept course for the intercept asset to the object        based on its trajectory (FIG. 3A).    -   If authorized, launch the intercept drone. This action is of        “low regret” because the operator can still over ride the        interceptor, however this allows the interceptor to close range        on the target.    -   The response planner can also take into consideration the 3D        site models as described herein.

Referring now to FIG. 2, a drone cuing system 210 is shown having aplurality of LIDAR sensors 10. LIDAR sensor 10 in one embodimentprovides 16 beams and has a range of approximately 100 meters. LIDARsensor 10 is disposed so that the beams 12 are pointed upward such thatthe beams 12 can detect an object, here drone 14 when the drone 14enters the range of the LIDAR sensor 10. The LIDAR sensor 10 is disposedon a surface and when the beam 12 is scanned from one horizon into theair to the other horizon creates a fan 16 that interrogates the airspace within the range of the LIDAR sensor 10. A plurality of sensors 10can be arranged along a line and networked together to provide alight-fence 18. By then disposing a plurality of light fences 18 aroundan area to be protected, a fence can be created to detect objectsentering the light fence 18. With such an arrangement, a detectionsystem 210 for a drone detection and tracking system for cuing atracking system is provided where a line scanning LIDAR is pointedupward to make a light-fence, and objects detected by the light-fencecan be used to cue a tracker. Several such light-fence sections can beestablished together around a perimeter of an asset to establish a lightfence around the asset. The inbound vector of an object can be given toa second LIDAR (flash, Geiger mode, line scanning) that is aimed toacquire and track the target to provide an accurate location. Once thetrack is acquired, the motion of the drone is used as input to maintainthe track of the target.

From the latter, it can be seen, a system according to the disclosureincludes a three dimensional line-scanner LIDAR sensor disposed on aside to provide a set of fanned beams that travel from one horizon intothe air to the other horizon to detect an object and create a track forthe object and a long range sensor can be provided to track the objectdetected by the line-scanner LIDAR sensor in response to an initialtrack of the object created by the line-scanner LIDAR sensor.

As described above, a system can be alerted when a drone is flyingthrough a vertical plane. Interested parties are alerted when a drone isinvading their space. By putting a line-scanning LIDAR on its side, aset of fanned beams are created that go from one horizon, into the air,and to the other horizon (left, up, right). Anything flying throughthese beams can be detected, and a track can be established. Thisbecomes a detection system that can cue another sensor like a long rangeLIDAR. By surrounding a valuable object (or location) with a lightfence, an alert can be provided whenever something flies into themonitored airspace. The system can be used to alert a long range LIDARto the presence of a drone so that the long range LIDAR can track it.Because of the narrow field of view, it is not practical for the longrange LIDAR to do detection. The light fence provides a technique fordetection and to provide an accurate location where the long range LIDARshould look.

It should be understood a line-scanning LIDAR is available from severalvendors to include models available such as a Velodyne VLP16, HDL32,SICK LMS 111, or a Quanergy M8. It should also be understood that theconcept of a light fence is well known in the art. In general to make alight fence: Turn on Lidar, Take a few scans for the Lidar to learn allthe expected return ranges for all beams at all angles. For example at132 degrees the light may travel 30 meters before reflecting off abranch. We know between 0-30 meters is open space because the beamreflected back at 30 meters. At 140 degrees there may not be any returnbecause the beam went up in the air and nothing reflected back. We storethis profile for each beam. When watching the fence you are looking fordeviation from the expected pattern. If at 132 degrees there is a returnat 18 meters, something has broken the open space and blocked the beambefore the expected 30 meter range. If at 140 degrees there is a returnat 93 meters, then an object has appeared at 93 meters that waspreviously open air. If the Lidar has multiple beams, several suchbreaks in different beams will establish a vector. By networking theLIDAR sensors together, a fence can be created to detect when an objectpenetrates the fence. Networking the lidars together is nothing morethan turning them all on with appropriate power and data connections.They do not need to know about each other, they can all operateindependently. To form a coordinate system around these sensors theyneed to be surveyed in, so that beam breakages can be translated into aglobal coordinate frame such as GPS.

Referring now also to FIG. 1, it should now be appreciated for the fanLIDAR, the detection is made by an object flying through the fan. Thedrone cuing system 210 gives best vector information to the trackingsensor 114 and target tracker (tracking controller) 116. The trackingcontroller 116 aims flash LIDAR to predicted track location and startshunting for the object in the sky. An object is segmented frombackground by being in open air. The object is tracked in LIDAR frameusing existing LIDAR tracking code and the tracking information is fedback into tracking controller 116. Optionally cameras can be aimed atthe track as well. LIDAR (and optional camera) data is given to humanoperator 122 to determine threat vs. non-threat or automated techniquescan be used as well. Sensor fusion techniques can also be used.

Referring now to FIG. 3, a tracking LIDAR 20 is shown where an ASC TigerCub Flash LIDAR emits a flash of laser light and uses a CCD to capturerange information. Field of view is narrow, like that of a camera. Thetracking LIDAR 20 pointed toward a target 26 will return an image 28 ofthe target 26. The range can be up to 1 km. At 1 km, pixels are about 20cm, at 500 m, pixels are about 10 cm, and at 100 m, pixels are about 2cm. A given inbound track from a cuing detection system 210 provides thelocation information of a target drone such that a tracking LIDAR 20 canscan the sky on a pan/tilt head to find a UAV or drone. Once an UAV isfound, the tracking LIDAR 20 can track the UAV, providing 3D coordinatesfor counter measures, provide a 3D model of the object forclassification, and give a clean view of an object to an operator forgo/no-go decision.

Referring now to FIG. 4, a drone detection and tracking system 200includes an early detection system provided by drone cuing system 210for detecting the presence of a drone. The cue sensor 10 facing upwarduses it's modality to detect the presence of drones. It should beappreciated that the initial detectors could be acoustic, infrared,radar or other sensors but here we are describing a LIDAR sensor. Forthe fan LIDAR sensor, the detection is made by vector flying through thefan. The cue sensor 10 from the early detection system 210 gives bestvector information to long range tracker 220. The long range tracker 220aims flash LIDAR to an object 222 to a predicted track location andstarts hunting for the object 222 in sky. The object 222 is segmentedfrom background by being in open air. The object 222 is tracked in LIDARframe using existing LIDAR tracking code and the tracking information isfed back into tracking controller of long range tracker 220. Optionallycameras can be aimed at the track as well. As described with FIG. 1,LIDAR (and optional camera) data is given to a human operator 122 todetermine threat vs. non-threat and automated techniques can be used aswell. Sensor fusion techniques can also be used.

Referring now to FIG. 5, a drone detection and tracking system 300 isshown where a line scanning LIDAR 310 is pointed upward to make alight-fence, and flying entities that fly through the light fenceestablish an inbound vector. Several such light-fence sections can beestablished together around the perimeter of an asset. The inboundvector is given to a second LIDAR 320 (flash, Geiger mode, linescanning) that is aimed to acquire and track the target to provide anaccurate location. Once the track is acquired, the motion of the droneis used as input to maintain the track of the target. As to be describedhereinafter in connections with FIG. 8, one or more intercept drones arethen tasked to the location of the first drone carrying a countermeasure device such as a localized jammer, or net, or net gun based onthe track from the ground based system.

Referring now to FIGS. 6 and 6A, a drone detection system 400 is shownto include a plurality of detection sensors 410 arranged to detect anobject, more specifically a drone 440. A detection processor 412captures the existence of an object and cues the presence of a drone toa tracking sensor 414 which acquires and tracks at long range the droneusing target tracker 416. An image of a target drone once cued andtracked can be fed to a target identifier 418 for target recognition andthe image 420 of the target is displayed to an operator 422 on display424 so the operator 422 can verify and analyze the target. The targettracker 416 also feeds the target tracks to a semi-autonomous responseplanner system 426 and with inputs also from the operator 422 candetermine countermeasures 428 appropriate for the target. The dronedetection system 400 also includes a system 430 for creating a threedimensional model of an environment where in the detection sensors 410and the tracking sensors 414 with the target identifier 418 provides ascanning system to scan an environment to provide an image 434 of thescanned environment, a geo-locator 452 is used to tag a plurality ofpoints within the image with geo-reference points and a labeler 454 isused to label features of interest within the image and to identifypossible access paths within the features of interest potentiallyproviding an access path for a target drone. Furthermore, a real-timepedestrian model system 432 is provided to track locations ofpedestrians in an environment 436. It should be noted the environment436 can include a portion of the image 434, include all of the image434, or include more than the environment captured by image 434.

It should be appreciated surveying a site by LIDAR to create a 3D modelof the environment can be used as input for: a) explaining falsepositives when detecting and tracking drones, b) calculating fields ofview when detecting and tracking drones, c) optimizing countermeasuresfor drones, and d) planning routes for countermeasures for drones. Usingknown methods, a 3D scan of the environment is made producing a detailedpoint cloud of fixed objects and points are Geo-referenced in thismodel. The model gets loaded into command and control software. Thecommand and control software is written to use this model when planningway points for interception by avoiding objects that are possiblecollisions (e.g trees) without requiring on board sensing. The model isused when reading and considering new tracks (from LIDAR or other sensor(e.g. radar, acoustics)) to determine if location of a new track islikely to really be from noise (traffic, waving flag, fireworks, . . . )or in fact a potential target. The model is used when evaluating blindspots of the system for deployed sensors by placing their location andfield of view into the model and tracing their field of view forintersections with fixed objects in the model (building, trees). Themodel is used when deciding the windows of opportunity for countermeasures and prioritizing their use by considering how long a window ofopportunity to intercept is possible, if there is collateral damage(pedestrians), chance of interference (radio tower, multi-path offbuilding), etc. based on modality (jamming, projectile, etc).

It should now be appreciated the system 400 can create a 3D model of theenvironment (buildings, trees, roads, parking lots, etc) and use thecontext of the world to perform better tracking, better false positiverejection, better intercept planning, perform obstacle avoidance for theintercept vehicle, better site preparation for a counter dronedetection, tracking and intercepting platform, for example, as shown inFIG. 6B. Using known methods, the system 400 can make a 3D scan of theenvironment producing a detailed point cloud of fixed objects and theobjects are geo-reference in this 3D scan model.

Referring now to FIG. 6A, a system for creating a three dimensionalmodel of an environment includes the 3D scene model 430 where a LIDARscanning system to scan an environment provides an image of the scannedenvironment which is stored as data 450 and a geo-locator 452 is used totag a plurality of points within the image with geo-reference points anda labeler 454 is used to label features of interest within the image andto identify possible access paths within the features of interestpotentially providing an access path for a target drone.

To implement the described technique, the system 400 scans theenvironment with a LIDAR detection sensor. This can be done by an aerialplatform, mobile mapping platform, or a stationary platform usingdetection sensors 410. See for example the image of the scenes in FIG.6B or FIG. 6C. Next, the system 400 geo-references the points in thescene with GPS using known techniques. This is common practice. Thesystem 400 will next label the scene with features of interest. Examplesinclude: roads (roads have cars, cars move); trees (trees sway in thewind, move slightly; trees are obstacles to avoid with drones);buildings (buildings are high value items we don't want to hurt); areaswith people (areas we want to avoid collateral damage); and otherfeatures of interest can be considered. Labeling of this data could bedone by hand or automated methods, or by geo referencing other datasources. Having the latter information available, a mission planner cannow consider placement of assets in the model as well as predict whereenemy drones may come from. A mission planner can consider windows ofopportunity for counter measures and analyze blind spots. The missionplanner can analyze areas where false positives (birds, for example) maycome from. By playing what-if scenarios, the mission planner can come upwith a better placement of assets to protect what needs protection.Furthermore, having the latter information available, when a track isfirst discovered, the mission planner can consider the likelihood it isa false track by where it originated from. For example, if it came froma tree, there is a possibility it may be a bird. Other sensors reportscan be considered. Acoustic solution detections can be evaluated in themodel, as well as radar detections, if desired. Radars may produce falsetracks off cars, etc. More false positives can be rejected byunderstanding where the false positives are originating from. With sucha technique, when a track is validated as a threat and countermeasureswill be launched, the mission planner can use the 3D model to plan whichcountermeasure can/should be launched, and determine when an opportunityto intercept is most likely. If the selected countermeasure is deployinganother drone, the mission planner can pilot an intercept drone aroundobstacles because the obstacles have been mapped in the scene apriori.Also with such a technique, if a counter measure may do collateraldamage (cause debris to fall, overshoot, jam RF in a cone, etc), themission planner can plan the best opportunity for minimal collateraldamage because a 3D model of the scene is available. The mission plannercan compute the firing angles, debris patterns, and effects of range ofvarious systems and choose to engage at a time and place likely to causethe least damage.

Referring now to FIGS. 6C and 6D, examples of a three dimensional sceneare shown. As described above, a geo-locator is used to tag a pluralityof points within the image with geo-reference points and a labeler isused to label features of interest within the image and to identifypossible access paths within the features of interest.

Referring now to FIG. 7, a screen shot 700 of a computer screen with anexample of a three dimensional scene 702 is shown. As described above, ageo-locator is used to tag a plurality of points within the image withgeo-reference points and a labeler is used to label features ofinterest.

Referring now to FIG. 8, to implement countermeasures to render a targetdrone 80 useless when the drone is identified as a nuisance or danger,an intercept drone 82 can be deployed. In certain embodiments, theintercept drone has on-board GPS and ability to fly to GPS locations;the intercept drone can receive waypoints by radio; the tracking systemis surveyed in so it's GPS location is known; the tracking system cantranslate track into GPS coordinates; the intercept drone is commandedover radio link to fly to GPS coordinates to put in range of a trackedtarget. Coordinates may be an offset or a projection from tracked target(above, ahead, below, etc). Trigger of a counter measure (jammer, net,etc) can be done automatically or by a human pressing button. To speeddeployment, an intercept drone 82 may be stationed at high altitude(˜400 ft) by tether to ground power, allowing it to stay in place 24hrs/day until needed to deploy—dropping ground tether and interceptingfrom above.

Referring now to FIG. 9, a drone detection system 500 is shown toinclude a plurality of detection sensors 510 arranged to detect anobject, more specifically a drone 502. A detection processor 512captures the existence of the drone 502 and cues the presence of thedrone 502 to a tracking sensor 514 which acquires and tracks at longrange the drone using target tracker 516. Target tracker 516 providestrack and the tracking sensor (514)'s GPS coordinates to command andcontrol processor 520 which in turn translates the track from sensorcoordinates into GPS coordinates and provides GPS coordinates of thedrone 502 to ground control station 522. Alternatively, the controlprocessor, knowing the current location of the intercept drone (526) inGPS coordinates through the ground control station (522), can determinea proper intercept course for the intercept drone 526, and command thevelocity and vector of travel for intercept drone 526 to intercept thedrone 502. The ground control station 522 then provides controls todrone controller 524 which controls an intercept drone 526. The groundcontrol station 522 also provides image data to a tablet 528 such as anAndroid Tactical Assault Kit (ATAK) tablet 528. The intercept drone 526has on-board GPS receiver and ability to fly to GPS locations and canreceive waypoints by radio. The tracking system is surveyed in so it'sGPS location is known. The tracking system can translate track into GPScoordinates. The intercept drone 526 is commanded over radio link 530 tofly to GPS coordinates to put in range of tracked target. Coordinatesmay be an offset or a projection from tracked target drone 502 (above,ahead, below, etc). The command and control processor 520 or the groundcontrol station 522 can then trigger a counter measure (jammer, net,etc) initiated automatically or by a human pressing a button.

With such an arrangement, a high powered intercept drone can be flownunder supervised autonomy of a system that is tracking a threat dronewith a long range LIDAR. The supervised autonomy is performed byprocessing the detection and tracking information, and sending commandinstructions to the intercept drone to fly to the location of the threatdrone. The location of the threat drone is updated by the trackingperformed by the long range LIDAR. The intercept drone can carry any ofa number of payloads that are appropriate to disable the threat when insufficient range. The present approach will allow for the interceptdrone to carry many different kinds of packages in close range to thetarget drone. By waiting until close range to the target before using acounter measure collateral damage can be minimized, jamming ranges canbe reduced to a few feet. By using an intercept drone, a human operatorcan safely abort the intercept after launch. By using a long rangeLIDAR, the intercept drone can be controlled at far ranges and maintainan accurate track of the target drone.

Referring now to FIG. 10, drone tracking is accomplished where a human90 designates a target drone 92 either by a pointing device (laserdesignator) 94 or an approximate coordinate and a second autonomousintercept drone 96 uses on board sensing (camera or range sensor beingtwo examples) 98 to follow first drone 92 after it has been selected asthe target. This is designed to allow a “first responder” (probably twoworking as a team) to get rid of a nuisance drone. The method ofdisabling the target is left open, as many different payloads couldexist. Target selection can be done by illumination using the pointingdevice 94, or giving an approximate GPS location (via an ATAK tablet 91or any available user device such as a smart phone or computer). Theintercept drone 96 gives back its understanding of the selected targetwhich is displayed on ATAK tablet 91 for human 90 to confirm. Theintercept drone 96 then self pilots to the location of the target. Theintercept drone 96 follows the motion of the target drone 92 to updatedestination GPS coordinates. Tracking can be done with a camera, LIDAR,or other sensor and the intercept drone 96 can use on board sensing orpre-loaded model for obstacle detection to include stereo vision, radar,lidar, ultrasound or the like. An inner loop of next step GPS waypoints, or a series of thrust commands in a vector, are given to aflight controller (standard robotics practice) to facilitate the courseof flight. Bearing and range can be used to project next the waypointand the status is updated on ATAK tablet 91. The human 90 (user) isallowed to pause, abort, aid the system, or trigger an onboard countermeasure (net, jammer, etc).

With such an arrangement, an indication of the target is provided withthe pointing device (Laser designator or draw on a screen) and feedbackis given to the user by communicating back to a tablet. The interceptdrone can be commanded without human intervention (self propelled) byusing supervised autonomy where the autonomous seek to destination withobstacle avoidance is provided to the flight path. The ATAK tabletprovides a user interface such that the drone gives back itsunderstanding of selected target which is displayed on ATAK tablet forhuman to confirm and to control the mission with a method of steering oraborting the process, if necessary. As described above, tracking donewith camera, LIDAR, or other sensor 98 where the drone self pilots tothe location of the target and the intercept drone 96 follows motion oftarget to update destination GPS coordinate using on board sensing orpre-loaded model for obstacle detection.

Referring again also to FIG. 9, instead of a human providing the initialtargeting as shown in FIG. 10, the drone detection system 500 caninclude the plurality of detection sensors 510 arranged to detect anobject or optionally a radar sensor or an acoustical sensor can be usedto initially detect an object, more specifically the drone 92. Onceinitially detected, the second autonomous intercept drone 96 uses onboard sensing (camera or range sensor being two examples) 98 to followfirst drone 92 after it has been selected as the target.

Referring to FIG. 11, a computer 540 includes a processor 552, avolatile memory 554, a non-volatile memory 556 (e.g., hard disk) and theuser interface (UI) 558 (e.g., a graphical user interface, a mouse, akeyboard, a display, touch screen and so forth). The non-volatile memory556 stores computer instructions 562, an operating system 566 and data568. In one example, the computer instructions 562 are executed by theprocessor 552 out of volatile memory 554 to perform all or part of theprocesses described herein.

The processes and techniques described herein are not limited to usewith the hardware and software of FIG. 11; they may find applicabilityin any computing or processing environment and with any type of machineor set of machines that is capable of running a computer program. Theprocesses described herein may be implemented in hardware, software, ora combination of the two. The processes described herein may beimplemented in computer programs executed on programmablecomputers/machines that each includes a processor, a non-transitorymachine-readable medium or other article of manufacture that is readableby the processor (including volatile and non-volatile memory and/orstorage elements), at least one input device, and one or more outputdevices. Program code may be applied to data entered using an inputdevice to perform any of the processes described herein and to generateoutput information.

The system may be implemented, at least in part, via a computer programproduct, (e.g., in a non-transitory machine-readable storage medium suchas, for example, a non-transitory computer-readable medium), forexecution by, or to control the operation of, data processing apparatus(e.g., a programmable processor, a computer, or multiple computers)).Each such program may be implemented in a high level procedural orobject-oriented programming language to communicate with a computersystem. However, the programs may be implemented in assembly or machinelanguage. The language may be a compiled or an interpreted language andit may be deployed in any form, including as a stand-alone program or asa module, component, subroutine, or other unit suitable for use in acomputing environment. A computer program may be deployed to be executedon one computer or on multiple computers at one site or distributedacross multiple sites and interconnected by a communication network. Acomputer program may be stored on a non-transitory machine-readablemedium that is readable by a general or special purpose programmablecomputer for configuring and operating the computer when thenon-transitory machine-readable medium is read by the computer toperform the processes described herein. For example, the processesdescribed herein may also be implemented as a non-transitorymachine-readable storage medium, configured with a computer program,where upon execution, instructions in the computer program cause thecomputer to operate in accordance with the processes. A non-transitorymachine-readable medium may include but is not limited to a hard drive,compact disc, flash memory, non-volatile memory, volatile memory,magnetic diskette and so forth but does not include a transitory signalper se.

The processes described herein are not limited to the specific examplesdescribed. Rather, any of the processing blocks as described above maybe re-ordered, combined or removed, performed in parallel or in serial,as necessary, to achieve the results set forth above.

The processing blocks associated with implementing the system may beperformed by one or more programmable processors executing one or morecomputer programs to perform the functions of the system. All or part ofthe system may be implemented as, special purpose logic circuitry (e.g.,an FPGA (field-programmable gate array) and/or an ASIC(application-specific integrated circuit)). All or part of the systemmay be implemented using electronic hardware circuitry that includeelectronic devices such as, for example, at least one of a processor, amemory, a programmable logic device or a logic gate.

Elements of different embodiments described herein may be combined toform other embodiments not specifically set forth above. Otherembodiments not specifically described herein are also within the scopeof the following claims.

What is claimed is:
 1. A system for creating a three dimensional modelof an environment comprising: a LIDAR scanning system to scan anenvironment to provide an image of a scene of the scanned environment; ageo-locator to tag a plurality of points within the image withgeo-reference points; and a labeler to label features of interest withinthe image of the scene and to identify possible access paths within thethree dimensional model of the environment from the features of interestpotentially providing an access path for a target drone.
 2. The systemas recited in claim 1 wherein the LIDAR scanning system comprises atracking system to track objects in the scanned environment and thetracking system determines if a new track is a false track by lookingwhere the track originated.
 3. The system as recited in claim 2 whereinthe tracking system generates an intercept track for an intercept dronefrom the possible access paths determined from the labeler and theenvironmental model.
 4. The system as recited in claim 1 comprising aresponse planner to plan safe paths through the environment for anintercept drone.
 5. The system as recited in claim 3 wherein theresponse planner includes identifying false positives.
 6. The system asrecited in claim 1 comprising a response planner to plan the placementof sensors within the environment to reduce blind spots in theenvironmental model.
 7. The system as recited in claim 1 comprising aresponse planner to plan interceptions that minimize collateral damage.8. The system as recited in claim 1 comprising a response planner toselect an appropriate countermeasure including deploying a second droneto intercept the target drone.
 9. The system as recited in claim 1comprising a response planner to pilot an intercept drone aroundobstacles that have been mapped in the scene apriori.
 10. A method ofproviding a three dimension model of an environment comprising: scanningan environment to provide an image of the scanned environment; tagging aplurality of points within the image with geo-reference points toidentify the location of a plurality of points; labeling features ofinterest within the image and identifying possible access paths withinthe three dimensional model of the environment from the features ofinterest potentially providing an access path for a target drone. 11.The method as recited in claim 10 comprising tracking objects in thescanned environment and determining if a new track is a false track bylooking where the track originated.
 12. The method as recited in claim10 comprising generating an intercept track for an intercept drone fromthe possible access paths determined from features of interest withinthe image.
 13. The method as recited in claim 10 comprising planningsafe paths through the environment for an intercept drone from thefeatures of interest within the image.
 14. The method as recited inclaim 12 comprising identifying false positives.
 15. The method asrecited in claim 10 comprising planning the placement of sensors withinthe environment to reduce blind spots in the environmental model. 16.The method as recited in claim 10 comprising planning interceptions thatminimize collateral damage.
 17. The method as recited in claim 10comprising selecting an appropriate countermeasure including deploying asecond drone to intercept the target drone.
 18. The method as recited inclaim 10 comprising piloting an intercept drone around obstacles thathave been mapped in the scene apriori.
 19. A drone detection systemcomprising: a LIDAR scanning system to scan an environment to provide animage of a scene of the scanned environment and to detect a target droneentering the scanned environment; a geo-locator to tag a plurality ofpoints within the image with geo-reference points; a labeler to labelfeatures of interest within the image of the scene and to identifypossible access paths within the three dimensional model of theenvironment from the features of interest potentially providing anaccess path for the target drone; and a response planner to select anappropriate countermeasure including deploying a second drone tointercept the target drone.
 20. The drone detection system as recited inclaim 19 comprises a tracking system to track objects in the scannedenvironment and wherein the tracking system generates an intercept trackfor an intercept drone from the possible access paths determined fromthe scanned environment.